Machine learning-based estimation of crude oil-nitrogen interfacial tension
Abstract Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In thi...
Saved in:
Main Authors: | Safia Obaidur Rab, Subhash Chandra, Abhinav Kumar, Pinank Patel, Mohammed Al-Farouni, Soumya V. Menon, Bandar R. Alsehli, Mamata Chahar, Manmeet Singh, Mahmood Kiani |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-85106-y |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Impact of gas composition, pressure, and temperature on interfacial Tension dynamics in CO₂-Enhanced oil recovery
by: Rahul Gajbhiye
Published: (2025-01-01) -
Experimental evaluation of nanoclay assisted water based EOR method
by: Hamid Mohammad Soleimani, et al.
Published: (2025-01-01) -
Interfacial tension reduction using nitrogen graphene quantum dots with various precursors, molar ratios, and synthesis durations for enhanced oil recovery
by: Younes Gholamzadeh, et al.
Published: (2024-12-01) -
The effects of the different crude protein levels on some blood metabolites in fattening türkgeldi male lambs
by: I. Yaman Yurtman, et al. -
Elit Türk kadın hentbolcularda 30 – 15 intermittent fitness test ile anaerobik performans ilişkisinin değerlendirilmesi
by: Goktug Ertetik, et al.
Published: (2023-12-01)